Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
A riemannian network for spd matrix learning
Abstract Symmetric Positive Definite (SPD) matrix learning methods have become popular in
many image and video processing tasks, thanks to their ability to learn appropriate statistical …
many image and video processing tasks, thanks to their ability to learn appropriate statistical …
SPD manifold deep metric learning for image set classification
By characterizing each image set as a nonsingular covariance matrix on the symmetric
positive definite (SPD) manifold, the approaches of visual content classification with image …
positive definite (SPD) manifold, the approaches of visual content classification with image …
First-order methods for geodesically convex optimization
Geodesic convexity generalizes the notion of (vector space) convexity to nonlinear metric
spaces. But unlike convex optimization, geodesically convex (g-convex) optimization is …
spaces. But unlike convex optimization, geodesically convex (g-convex) optimization is …
Log-euclidean metric learning on symmetric positive definite manifold with application to image set classification
Abstract The manifold of Symmetric Positive Definite (SPD) matrices has been successfully
used for data representation in image set classification. By endowing the SPD manifold with …
used for data representation in image set classification. By endowing the SPD manifold with …
Research on mobile impulse purchase intention in the perspective of system users during COVID-19
W Zhang, X Leng, S Liu - Personal and Ubiquitous Computing, 2023 - Springer
COVID-19 has caused a serious impact on the global economy. Effectively stimulating
consumption has become a momentous mission in responding to the impact of the …
consumption has become a momentous mission in responding to the impact of the …
Kernel methods on Riemannian manifolds with Gaussian RBF kernels
In this paper, we develop an approach to exploiting kernel methods with manifold-valued
data. In many computer vision problems, the data can be naturally represented as points on …
data. In many computer vision problems, the data can be naturally represented as points on …
Kernel methods on the Riemannian manifold of symmetric positive definite matrices
Abstract Symmetric Positive Definite (SPD) matrices have become popular to encode image
information. Accounting for the geometry of the Riemannian manifold of SPD matrices has …
information. Accounting for the geometry of the Riemannian manifold of SPD matrices has …
From manifold to manifold: Geometry-aware dimensionality reduction for SPD matrices
Representing images and videos with Symmetric Positive Definite (SPD) matrices and
considering the Riemannian geometry of the resulting space has proven beneficial for many …
considering the Riemannian geometry of the resulting space has proven beneficial for many …